[pubname] => MATCH Communications in Mathematical and in Computer Chemistry

[pubkey] => 0340-6253

[workinfo] => 71(1): 149-172

[year] => 2014

[title] => Structure-activity relationships from natural evolution

[authors] => Sorana D. BOLBOACĂ, Daniela D. ROŞCA, Lorentz JÄNTSCHI

[abstract] =>
Structure-activity relationships emulate the adaptation of chemical compounds to the biological environment. When a family of descriptors derived from a skeleton using different mathematical operations and physical properties is involved, the search space for structure-activity relationships is constructed in a natural way. A genetic algorithm implementing different selection and survival strategies, an unexplored issue, was designed and it is presented. A comparison of evolutionary strategies was conducted on a series of 206 polychlorinated biphenyls with known values of octan-1-ol/H2O partition coefficients, on which a Molecular Descriptors Family (MDF) was generated as the search space. The obtained results showed that the implemented genetic algorithm proved to be a reliable method of finding optimal multiple-linear regression models that are able to explain relationships between structure and activity. The results showed that different tournament selection and proportional survival provide the solution closest to the one obtained by complete search. Furthermore, the results revealed that, in general, every pair of survival and selection strategies pushes evolution on significantly different paths and may form the basis of phylogeny analysis.